In industrial control systems, the utilization of deep learning based methods achieves improvements for anomaly detection. However, most current methods ignore the association of inner components in industrial control systems. In industrial control systems, an anomaly component may affect the neighboring components; therefore, the connective relationship can help us to detect anomalies effectively. In this paper, we propose a centrality-aware graph convolution network (CAGCN) for anomaly detection in industrial control systems. Unlike the traditional graph convolution network (GCN) model, we utilize the concept of centrality to enhance the ability of graph convolution networks to deal with the inner relationship in industrial control systems. Our experiments show that compared with GCN, our CAGCN has a better ability to utilize this relationship between components in industrial control systems. The performances of the model are evaluated on the Secure Water Treatment (SWaT) dataset and the Water Distribution (WADI) dataset, the two most common industrial control systems datasets in the field of industrial anomaly detection. The experimental results show that our CAGCN achieves better results on precision, recall, and F1 score than the state-of-the-art methods.

How to maximize the advantages of in-network caching under limited cache space has always been a key issue in information-centric networking (ICN). Replica placement strategies aim to fully utilize cache resources by optimizing the location and quantity distribution of replicas in the network, thereby improving the performance of the cache system. However, existing research primarily focuses on optimizing the placement of replicas along the content delivery path, which cannot avoid the inherent drawback of not being able to leverage off-path cache resources. The proposals for off-path caching cannot effectively solve this problem as they introduce excessive complexity and cooperation costs. In this paper, we address the trade-off between cache resource utilization and cooperation costs by introducing a mechanism complementary to replica placement. Instead of redesigning a new caching strategy from scratch, we propose a proactive cooperative caching mechanism (called RMBCC) that involves an independent replica migration process, through which we proactively relocate replicas evicted from the local cache to neighboring nodes with sufficient cache resources. The cooperation costs are effectively controlled through migration replica filtering, migration distance limitation, as well as hop-by-hop migration request propagation. Extensive simulation experiments show that RMBCC can be efficiently integrated with different on-path caching strategies. Compared with representative caching schemes, RMBCC achieves significant improvements in evaluation metrics such as cache hit ratio and content retrieval time, while only introducing negligible cooperation overhead.

Traditional internet protocol (IP) networks, adhering to a “best-effort” service model, typically utilize shortest-path routing for data transmission. Nevertheless, this methodology encounters limitations, especially considering the increasing demands for both high reliability and high bandwidth. These demands reveal shortcomings in this routing strategy, notably its inefficient bandwidth utilization and fault recovery capabilities. The method of multipath transmission has been extensively researched as a solution to these challenges. With the emergence of innovative Internet architectures, notably information-centric networking (ICN), network nodes have gained enhanced capabilities, opening new avenues for multipath transmission design. This paper introduces a multipath scheduling approach for network nodes, capitalizing on the advanced features of these modern nodes. It reimagines the conventional next-hop node as a group of potential next-hop nodes based on both global and local routing strategies and assigns traffic shares to each node within this group for balanced traffic distribution. Network nodes are configured to periodically review and adjust traffic shares according to the link statuses. If scheduling cannot be completed within the set, feedback is sent to upstream nodes. Simulations demonstrate that this approach effectively leverages network path variety, improves bandwidth usage and throughput, and minimizes average data transmission time.

The control of transmission rates is currently a major topic in network research, as it plays a significant role in determining network performance. Traditional network design principles suggest that network nodes should only be responsible for forwarding data, while the sending node should manage control. However, sending nodes often lack information about network resources and must use slow-start algorithms to increase the transmission rate, potentially leading to wasted bandwidth and network congestion. Furthermore, incorrect judgments about network congestion by sending nodes may further reduce network throughput. The emergence of new Internet architectures, such as information-centric networks (ICNn), has empowered network nodes with more capabilities, including computation and caching. This paper proposes a method for transmission rate control that actively avoids congestion through network node bandwidth allocation. The sending, network, and receiving nodes each calculate the available transmission rate, and the sending node negotiates with the other nodes through a rate negotiation message to obtain the maximum transmission rate possible given the current state of the network. The network nodes notify the sending node to adjust the transmission rate to adapt to changes in the network through a rate adjustment message. Simulation experiments show that the proposed method is better than traditional methods in reducing network congestion, providing a stable transmission rate, increasing the network throughput capacity, and improving performance in high-latency and high-bandwidth networks. Additionally, the proposed transmission rate control method is fairer than traditional methods.

随着软件定义网络(SDN)规模的扩大,交换机与控制器间的响应时延逐渐成为网络性能的瓶颈.为了保证大规模网络中时延敏感型应用的时延需求,提出了一种两级分层控制平面架构的优化方案.在层次化架构的基础上重新设计了部分控制器的内部结构,模块化的设计思想使其具备灵活的控制策略;通过订阅转发模式,大幅度提升了北向通信的效率,为降低响应时延做出了保障;设计了基于网络服务标准化参数、与VIKOR方法相结合的应用程序调度决策模型,用于在资源受限的情况下尽可能满足多的应用程序对于网络资源的需求.通过对比实验,验证了经过优化后的架构时延对比传统框架下降3.66％～14.39％.

随着工控网络信息化程度的不断提高,工控网络逐渐变得更加开放,一方面给工业生产提供了便捷,但另一方面也带来了安全隐患.工控网络作为重要的基础设施,一旦受到攻击将产生严重损害.近年来不少学者使用网络异常检测技术来发现工控网络中潜在的安全隐患,取得不错的成果.然而工控网络中的数据往往缺少标注,这限制了传统监督学习类算法在工控网络安全领域的应用.基于非监督学习的算法可以在缺少标注的场景下实现异常检测,但是往往存在算法性能较差的问题,而迁移学习类算法可以通过在源域上学习后迁移到只有少量标注的目标域实现在少标注情况下的较高性能.为了进一步提高在缺少标注的工控网络中进行异常检测的性能,本文提出一种工控网络异常检测中基于灵敏度的动态迁移算法.首先该算法基于迁移学习的思想,在有标注的源域中进行训练后迁移到缺乏标注的目标域,可以在缺少标注的工控网络环境下进行异常检测.其次得益于门控循环单元的记忆效应,该算法可以有效利用工控网络数据内在的时序关联性,进一步提高算法异常检测的能力.同时该算法中的基于参数灵敏度因子对参数进行动态迁移的方法,改进了传统迁移学习微调方法对源域和目标域数据底层特征学习不均衡的不足.在KDD99数据集和Kyoto2016数据集上的对比实验表明,该算法采用的基于灵敏度的动态迁移学习方法对比传统微调方法具有更好的效果.在与最新一系列无监督与迁移学习算法的对比中,该算法在精确率、召回率和综合性的F1分数上均优于对比方法,取得了0.97、0.95、0.96的优秀性能.

信息中心网络(ICN)是一种满足海量内容的数据分发需求的新型网络架构.在ICN中,用户向网络发送请求报文,网络中的缓存副本节点则会响应请求回复数据报文.请求报文与数据报文的流量是ICN中2种截然不同的流量类型.在网络发生拥塞时,为保证传输效率,需要区分处理不同特点的流量.针对ICN网络的延迟保障与带宽利用率问题,提出了一种区分报文类型的主动队列管理AQM算法.该算法通过对2种流量执行主动丢包操作,使2种流量趋于一个合理的状态.基于对2种流量被主动丢包的概率根据统计的2种报文流量占用带宽的大小结合比例积分控制器计算得出.同时,通过报文调度器优先调度对请求报文减少数据传输的往返时间.实验表明,提出的AQM算法能够合理分配2种报文占用的带宽,提高网络严重拥塞时数据传输的吞吐量,减少完成时间,降低往返时间.

Many applications suitable for multicast transmission, such as video conferencing and live e-commerce, demand high Quality of Service (QoS) and require data delivery to be completed within specified delay constraints. Some methods have been proposed for constructing delay-constrained multicast routing based on network state. However, obtaining precise network latency can be challenging, resulting in inaccuracies in delay-constrained routing calculations and, ultimately, the inability to meet application requirements. Additionally, many methods engage in an indiscriminate exploration of potential paths in the network, causing significant message processing overhead. This paper proposes an Information-Centric Networking (ICN)-based approach for delay-constrained multicast routing. Our method dynamically constructs multicast paths from tree nodes to receivers based on real-time path status detection during the join message propagation phase. Additionally, we present a method for acquiring neighborhood state information to facilitate real-time routing decisions. To curtail indiscriminate path exploration, our approach uses the ICN Name Resolution System (NRS) to obtain and select potential optimal tree nodes. For this purpose, we design a multicast service registration and resolution mechanism using the ICN Name Resolution System (NRS). Simulation results indicate that our approach exhibits a higher success ratio and concurrently incurs lower message processing overhead than some other methods, particularly in situations with stringent delay constraints.

As the Internet communication model changes from host-centric to content-centric, information-centric networking (ICN) as a new network architecture has received increasing attention. There are often multiple replicas of content in ICN, and how to reasonably utilize the characteristics of multiple replicas to further improve user experience is an important issue. In this paper, we propose a replica-selection algorithm, called the transmission completion time estimation (TCTE) algorithm. TCTE maintains the state of replica nodes in the domain with passive measurements in a limited domain of an enhanced name resolution system (ENRS), then estimates the transmission completion time of different replica nodes and selects the smallest one. When no replica is found in the ENRS domain, the nearest-replica algorithm will be used, so TCTE will not increase the traffic in the core network. Experiments show that TCTE not only effectively improves the user’s download rate and edge node throughput, reduces download rate fluctuations, reduces user download delay, and improves fairness, but also has universal applicability.

Due to the overload of IP semantics, the traditional TCP/IP network has a number of problems in scalability, mobility, and security. In this context, information-centric networking (ICN) is proposed to solve these problems. To reduce the cost of deployment and smoothly evolve, the ICN architecture needs to be compatible with existing IP infrastructure. However, the rigid underlying IP routing regulation limits the data transmission efficiency of ICN. In this paper, we propose a novel multipath transmission scheme by utilizing the characteristics and functions of ICN to enhance data transmission. The process of multipath transmission can be regarded as a service, and a multipath transmission service ID (MPSID) is assigned. By using the ICN routers bound to the MPSID as relay nodes, multiple parallel paths between the data source and the receiver are constructed. Moreover, we design a path management mechanism, including path selection and path switching. It can determine the initial path based on historical transmission information and switch to other optimal paths according to the congestion degree during transmission. The experimental results show that our proposed method can improve the average throughput and reduce the average flow completion time and the average chunk completion time.

Information-Centric Networking (ICN) has revolutionized the manner of content acquisition by shifting the communication mode from host-centric to information-centric. Considering the existing, large amount of IP infrastructure in current networks, the new ICN architecture is proposed to be compatible with existing networks in order to reduce deployment cost. However, due to compatibility with IP networks, ICN data packets must be transmitted through the default path provided by IP routing regulations, which also limits the transmission efficiency and reliability of ICN. In order to address this issue, this paper introduces a multipath transmission method applied in ICN which takes full advantage of the functions and characteristics of ICN and builds multiple end-to-end relay paths by using the ICN routers as relay nodes. We then propose a relay-node-selection algorithm based on path correlation to minimize the impact of overlapping links. Moreover, we comprehensively calculate the path state value by combining the round-trip time and packet loss rate and propose a multipath data-scheduling algorithm based on the path state value. Simulation experiments show that the proposed method can maintain high bandwidth utilization while reducing the number of out-of-order packets.

Network layer multicast research is an important field of network research that requires simulators or emulators to support Software-Defined Networking (SDN) as well as to provide a specific structure at the network layer to facilitate packet forwarding, such as a multicast tree. The existing emulation platforms cannot effectively support the emulation of certain key multicast technologies, such as the Grafting Point (GP)-selection method and Rendezvous Point (RP)-selection method, for the following reasons: First, the programmable data plane of the existing emulation platform has many defects, such as the inability to process packet scheduling tasks, the prohibition of dynamic memory allocation and loops with unknown iteration counts, which make it difficult to deploy complex multicast protocols and algorithms. Secondly, at present, no emulation platform integrates network layer multicast emulation functions. As a result, users need to develop the multicast tree construction and maintenance mechanism in advance, which makes experiments laborious. To solve the above problems, based on NS4, we designed a multicast emulation platform, M-Emu. M-Emu presents a Service-Forwarding Architecture, which enables the data plane to deploy arbitrary complex protocols and algorithms. Based on the Service-Forwarding Architecture, M-Emu integrates a Multicast-Emulation Framework, which has a complete multicast tree construction and maintenance mechanism. We explain in detail how the various parts of M-Emu cooperate to complete the multicast emulation with an example and prove that M-Emu is efficient in CPU and memory consumption, etc., through a large number of experiments.

As a new network architecture, information-centric networking (ICN) decouples the identifiers and locators of network entities and makes full use of in-network cache technology to improve the content distribution efficiency. For reliable multicast, ICN in-network cache can help reduce the loss recovery delay. However, with the development of applications and services, a multicast tree node often serves multiple reliable multicast groups. How to reasonably allocate cache resources for each multicast group will greatly affect the performance of reliable multicast. In order to improve the overall loss recovery performance of reliable multicast, this paper designs a dynamic cache allocation mechanism (DCAM). DCAM considers the packet loss probability, the node depth of the multicast tree, and the multicast transmission rate of multicast group, and then allocates cache space for multicast group based on the normalized cache quota weight. We also explore the performance of three cache allocation mechanisms (DCAM, AARM, and Equal) combined with four cache strategies (LCE, CAPC, Prob, and ProbCache), respectively. Experimental results show that DCAM can adjust cache allocation results in time according to network changes, and its combinations with various cache strategies outperform other combinations. Moreover, the combination of DCAM and CAPC can achieve optimal performance in loss recovery delay, cache hit ratio, transmission completion time, and overhead.

Software-defined network separates the control plane and the data plane, making the network more flexible. With the expansion of the network scale, one centralized controller cannot meet the latency needs of large-scale networks. Therefore, it is necessary to use multicontroller architecture, which has some problems with the controller placement. In this article, we take both the average latency and the worst latency between switch and controller into consideration and make a multi-objective optimization model. An improved label propagation algorithm based on traffic gravitation is proposed to solve the subdomain division problem, and a heuristic method is for subdomain controller placement. The simulation experiments show the effectiveness of the proposed algorithm and the time complexity guarantee for large-scale networks.

Ubiquitous in-network caching plays an important role in improving the efficiency of content access and distribution in Information-Centric Networks (ICN). Content placement strategies, which determine the location distribution of content replicas in the network, have a decisive impact on the performance of the cache system. Existing strategies primarily focus on pushing popular content to the network edge, aiming to improve the overall cache hit ratio while neglecting to effectively balance the traffic load between network links; this leads to insufficient utilization of network bandwidth resources and further excessive content delivery time and user QoE degradation. In this paper, a Path Load-Aware Based Caching strategy (PLABC) is proposed, in which content-related information and dynamic network-related information are comprehensively considered to make cache decisions. Specifically, the utility of caching the content at each on-path node is calculated according to the bandwidth consumption savings and the load level of the transmission path, and the node with the greatest utility value is selected as the caching node. Extensive simulations are conducted to compare the performance of PLABC with other state-of-the-art schemes by quantitative analysis. Simulation results validate the PLABC strategy’s effectiveness, especially in balancing link load and reducing content delivery time.

To fundamentally improve the efficiency of content distribution in the network, information-centric networking (ICN) has received extensive attention. However, the existence of a large number of IP facilities in the current network makes the smooth evolution of the network architecture a realistic requirement. The ICN architecture that separates the process of name resolution and message routing is widely accepted for its better compatibility with IP networks. In this architecture, the user first obtains the locator of the content replica node from the name resolution system (NRS) and then completes the data transmission through the locator. In data transmission, receiver-driven congestion control algorithms need to be studied. Therefore, we introduce the Copa algorithm into ICN and propose an improved Copa-ICN algorithm. Experiments show that the Copa-ICN algorithm has a high convergence speed and fairness, and when there is a transmission process in the opposite direction, it can still have a high throughput different from the original Copa algorithm.

Information-centric networking (ICN) is expected to be a candidate for future internet architecture, and it supports features such as multicast that improves bandwidth utilization and transmission efficiency. However, multicast itself does not provide congestion control. When multiple multicast groups coexist, multicast traffic may exhaust all network resources, and cause network congestion and packet loss. Additionally, traditional IP multicast congestion control mechanisms cannot be directly applied to ICN architecture. Therefore, it is necessary to consider an effective congestion control mechanism for ICN multicast. This paper proposes a single-rate multicast congestion control mechanism, called SRMCC. It supports router-assisted awareness of the network congestion state and congestion control message aggregation. Moreover, the fair shared rate estimation method is innovatively proposed to achieve protocol fairness. Most importantly, it adjusts the rate according to different congestion states indicated by the queue occupancy ratio. By introducing a rate selection factor, it can achieve a balance between packet loss rate and throughput. Experimental results show that our proposal outperforms other mechanisms in throughput, packet loss rate, total bandwidth utilization, and overhead, and achieves protocol fairness and better TCP friendliness.

Reliable multicast distribution is essential for some applications such as Internet of Things (IoT) alarm information and important file distribution. Traditional IP reliable multicast usually relies on multicast source retransmission for recovery losses, causing huge recovery delay and redundancy. Moreover, feedback implosion tends to occur towards multicast source as the number of receivers grows. Information-Centric Networking (ICN) is an emerging network architecture that is efficient in content distribution by supporting multicast and in-network caching. Although ubiquitous in-network caching provides nearby retransmission, the design of cache strategy greatly affects the performance of loss recovery. Therefore, how to recover losses efficiently and quickly is an urgent problem to be solved in ICN reliable multicast. In this paper, we first propose an overview architecture of ICN-based reliable multicast and formulate a problem using recovery delay as the optimization target. Based on the architecture, we present a Congestion-Aware Probabilistic Cache (CAPC) strategy to reduce recovery delay by caching recently transmitted chunks during multicast transmission. Then, we propose NACK feedback aggregation and recovery isolation scheme to decrease recovery overhead. Finally, experimental results show that our proposal can achieve fully reliable multicast and outperforms other approaches in recovery delay, cache hit ratio, transmission completion time, and overhead.

In large bandwidth delay product (BDP) networks, standard slow-start algorithm has exponentially increasing congestion window, but is still increasingly difficult to meet the demand for fast utilization of bandwidth. The hindsight of standard slow-start algorithms on network congestion often results in significant packet loss as well. This phenomenon has become increasingly serious with the upgrading of network devices and the widespread deployment of the Internet. In this paper, we proposed the enhanced slow-start (ESS). ESS rapidly increases the congestion window (CWND) at a higher rate than the standard slow-start algorithm and stops the window growth in time when the window grows to a suitable value. Our simulation evaluation in NS3 shows that ESS has better performance in terms of bandwidth utilization compared to several widely used slow-start algorithms.

As one of the candidates for future network architecture, Information-Centric Networking (ICN) has revolutionized the manner of content retrieval by transforming the communication mode from host-centric to information-centric. Unlike a traditional TCP/IP network, ICN uses a location-independent name to identify content and takes a receiver-driven model to retrieve the content. Moreover, ICN routers not only perform a forwarding function but also act as content providers due to pervasive in-network caching. The network traffic is more complicated and routers are more prone to congestion. These distinguished characteristics pose new challenges to ICN transmission control mechanism. In this paper, we propose an effective transmission scheme by combining the receiver-driven transport protocol and the router-driven congestion detection mechanism. We first outline the process of content retrieval and transmission in an IP-compatible ICN architecture and propose a practical receiver-driven transport protocol. Then, we present an early congestion detection mechanism applied on ICN routers based on an improved Active Queue Management (AQM) algorithm and design a receiver-driven congestion control algorithm. Finally, experiment results show that the proposed transmission scheme can maintain high bandwidth utilization and significantly reduce transmission delay and packet loss rate.